JOURNAL ARTICLE

Near infrared band of Landsat 8 as water index: a case study around Cordova and Lapu-Lapu City, Cebu, Philippines

Abstract

Monitoring water bodies by extraction using water indexes from remotely sensed images has proven to be effective in delineating surface water against its surrounding. This study tested and assessed the Normalized Difference Water Index, Modified Normalized Difference Water Index, Automated Water Extraction Index, and near infrared (NIR) band using Landsat 8 imagery acquired on September 3, 2016. The threshold method was adapted for surface water extraction. To avoid over and under-estimation of threshold values, the optimum threshold value of each of the water indexes was obtained by implementing a geoprocessing model. Examining images of Landsat 8, NIR band has the largest difference in reflectance values between water and non-water bodies. Thus, NIR band exhibits the highest contrast between water and non-water bodies. An optimum threshold value of 0.128 for NIR band achieved an overall accuracy (OA) and kappa hat (Khat) coefficient of 99.3% and 0.986, respectively. NIR band of Landsat 8 as water index was found more satisfactory in extracting water bodies compared to the multi-band water indexes. This study shows that the optimum threshold values of each of the water indexes considered in this study were determined conveniently, where highest value of OA and Khat coefficient were obtained by creating and implementing a graphical modeler in Quantum Geographic Information System that automates from setting threshold value to accuracy assessment. This study confirms that remote sensing can extract or delineate water bodies rapidly, repeatedly and accurately.

Keywords:
Threshold limit value Surface water Reflectivity Water extraction Near-infrared spectroscopy Extraction (chemistry) Geoprocessing Spectroradiometer

Metrics

0
Cited By
0.00
FWCI (Field Weighted Citation Impact)
0
Refs
0.39
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Flood Risk Assessment and Management
Physical Sciences →  Environmental Science →  Global and Planetary Change
Remote Sensing in Agriculture
Physical Sciences →  Environmental Science →  Ecology
Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology

Related Documents

© 2026 ScienceGate Book Chapters — All rights reserved.